Conference Agenda

With the increasing insertion of AI tools in creative work in recent years, concerns about misinterpreting creativity and rendering designers obsolete are growing. Moreover, progress in AI predominantly comes from computer science, often resulting in misconceptions about graphic design. In particular, when it comes to highly specialized practices like identity design, the use of AI often remains too generic and fails to reflect the diversity employed by designers in their practice, propagating the homogenization of trends in graphical artefacts. This paper aims to bridge the discourse and methodological gap between computer science and graphic design by presenting a detailed exploration of the creative process in identity design. Based on grounded theory interviews with 20 graphic designers, it identifies key phases where AI augmentation can be inserted to enhance co-creativity. We conclude by offering insights on potential new directions for hybrid research in the fields of graphic design and informatics.

This study explores the changing skills of industrial designers in the age of Generative Artificial Intelligence (GenAI). It combines a systematic literature review covering 2020–2025 with a practice based investigation involving six designers who actively use GenAI in their design processes. Focusing on both novice and expert designers, the study examines how GenAI influences skill development through the lenses of upskilling, reskilling, and deskilling. The findings show that while GenAI enhances creativity, idea generation, and visualization, it also brings challenges such as increased cognitive load, information reliability issues, and a decline in production awareness. Differences between novice and expert designers reveal that experience level plays a key role in how GenAI driven transformations affect design skills. Overall, the study demonstrates that GenAI not only accelerates creative processes but also reshapes the cognitive and practical dimensions of industrial design practice.

This paper presents the Imagery Modes framework for analysing the designer–genAI interaction, complementing established metaphor-based accounts. Developed through Constructivist Grounded Theory and structured using Activity Theory, the framework focuses on the micro-dynamics of a single input–output exchange. It identifies four sequential sub-actions—crafting, processing, generating, and evaluating—that trace the relations between subjects (designer, genAI) and instruments (input, output). Central to the framework is the concept of “output imagery”, defined as the clarity with which the designer envisions the expected output prior to the interaction. Three modes of interaction are identified: Before, During, and After Imagery. The findings highlight the fluid and non-linear character of the designer-genAI interaction, showing how designers shift between modes across sequences. Finally, the framework clarifies the interplay between agency and sense of agency, showing that while agency varies linearly, sense of agency depends on alignment between expectations and outputs within each mode.

This paper presents a vocabulary for co-speculation with AI, developed

through an experimental design studio with 55 postgraduate students who used

generative AI tools to explore more-than-human design practices of decentering.

The vocabulary spans multiple scales of interaction—from individual prompting

acts to extended collaborative sessions—serving descriptive, analytic, and

generative functions. Whilst it was developed through the specific context of

decentering practices, we argue that this vocabulary is transferable to diverse

design domains. It offers designers and researchers a framework for more

reflective and intentional engagements with AI, contributing to emerging

discussions on how design practice evolves when speculation becomes a shared

activity between humans and machines.

As artificial intelligence evolves into agentic, adaptive, and generative systems, design research faces an epistemic shift. AI assistants, once reactive interfaces, are increasingly experienced as proactive presences that shape everyday life. This transformation reframes trust, no longer limited to technical reliability, transparency, or explainability, but also emerging as a relational and experiential phenomenon formed through interaction. While industry emphasizes technical trust, including privacy, security, and system reliability, design research must also address experiential trust, a felt confidence grounded in the lived quality of human and AI coexistence. Focusing on the smart home as a case of everyday domestic life, where these dynamics are visible, this paper introduces an experiential trust paradigm that repositions trust as an embodied, relational process. It contributes a framework for design research in the age of agentic AI by distinguishing experiential trust from technical trust and proposing new directions for designing trustworthy, co-living AI companions.

AI uncertainty has been proposed as a design material that provides practitioners with a foothold to engage with technical attributes of these technologies beyond any given output. However, it is unclear what role AI uncertainty can play in tangible product design processes. In this paper, we investigate this through two design research projects following a studio methodology; combining first-person reflective making with autoethnographic elements, incorporating a variety of AI technologies (e.g., object detection, image and video generation, mesh extraction). Through the analysis of these first-person accounts and reflection on design processes and outcomes, we find qualitatively different types of uncertainties manifesting across design methods and materialisation. As our contributions, we present (1) methodological and practice-oriented insights on the potential of specific affordances of AI uncertainty for tangible product design and (2) a discussion of the value of employing hands-on, studio-type design research in the aftermath of generative AI.